Food and Beverage Demand Forecasting with Power BI
A large UK food and beverage retailer improved demand forecasting by implementing a Power BI-based solution with Zelite. Using historical sales data and machine learning, the solution provided accurate long-term and short-term forecasts via interactive dashboards, reducing stock shortages, waste, staffing issues, and missed marketing opportunities.
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This case study explores how Zelite implemented a Power BI-based demand forecasting solution for a large UK food and beverage retailer with over 20 stores. The client sought to improve their ability to predict customer demand, allowing them to optimize stock levels, staffing, and revenue forecasts.
The implemented solution leveraged historical sales data, incorporating machine learning for iterative improvement, and delivered forecasts accessible through user-friendly dashboards on desktop and mobile devices. This empowered the client to make data-driven decisions regarding inventory control, cash flow management, staffing allocation, and marketing strategies.
The client, a leading UK food and beverage retailer with over 100 stores, faced the challenge of accurately predicting customer demand. Inefficient forecasting resulted in:
- Inaccurate inventory control, leading to stock shortages or excessive waste.
- Difficulty in managing cash flow due to unpredictable revenue streams.
- Under or over-staffing due to fluctuations in customer traffic.
- Missed marketing opportunities due to a lack of understanding of customer buying patterns.
To address these challenges, the client sought a solution that could:
- Predict customer demand: Accurately forecast future sales to optimize stock levels and staffing needs.
- Improve cash flow management: Gain insights into expected revenue to make informed financial decisions.
- Optimize marketing strategies: Leverage demand insights to inform promotional campaigns, pricing strategies, and product mix.
Zelite implemented a demand forecasting solution using Microsoft Power BI. This solution offered the following functionalities:
Data Integration:
Power BI integrated with the client's existing sales data warehouse, allowing for seamless access to historical sales data.
Machine Learning Model:
An iterative machine learning model was developed to analyze historical sales data and identify patterns. This model continuously improved its accuracy over time as it incorporated new data points.
Visual Analytics Dashboards:
Interactive dashboards were created within Power BI, showcasing forecasted sales data. These dashboards were accessible on both desktop and mobile devices, allowing for on-the-go decision making.
The dashboards included visualizations for:
- Long-term food and beverage sales forecasts.
- Short-term forecasts: Daily sales forecasts displayed in a line chart format.
- Short-term forecasts: Hourly sales forecasts displayed in a heat map format.
- Forecast Accuracy: This section tracked the model's accuracy over time, allowing for continuous improvement.
The Power BI-based demand forecasting solution delivered significant benefits for the client:
- Reduced Waste and Improved Inventory Control: Accurate forecasts enabled the client to optimize stock levels, minimizing stockouts and reducing food waste.
- Enhanced Cash Flow Management: Data-driven insights into future revenue streams empowered the client to make informed financial decisions and optimize cash flow.
- Optimized Staffing: By anticipating customer traffic, the client could effectively allocate staff, ensuring adequate personnel during peak hours and avoiding unnecessary costs during slower periods.
- Data-Driven Marketing: Insights from the demand forecasts allowed the client to tailor marketing campaigns, pricing strategies, and product offerings to better meet customer needs and preferences.
- Improved Decision Making: User-friendly dashboards provided actionable insights, empowering employees at all levels to make data-driven decisions across the organization.
By implementing a Power BI-based demand forecasting solution, Zelite empowered the UK food and beverage retailer to gain a deeper understanding of customer demand. This improved decision-making across the organization, leading to optimized inventory control, cash flow management, staffing strategies, and marketing initiatives. The iterative machine learning model ensured that the solution's accuracy would continue to improve over time, providing the client with a long-term competitive advantage.
